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  <h1>Source code for torch._tensor_str</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">math</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torch._six</span> <span class="kn">import</span> <span class="n">inf</span>


<span class="k">class</span> <span class="nc">__PrinterOptions</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="n">precision</span> <span class="o">=</span> <span class="mi">4</span>
    <span class="n">threshold</span> <span class="o">=</span> <span class="mi">1000</span>
    <span class="n">edgeitems</span> <span class="o">=</span> <span class="mi">3</span>
    <span class="n">linewidth</span> <span class="o">=</span> <span class="mi">80</span>
    <span class="n">sci_mode</span> <span class="o">=</span> <span class="kc">None</span>


<span class="n">PRINT_OPTS</span> <span class="o">=</span> <span class="n">__PrinterOptions</span><span class="p">()</span>


<span class="c1"># We could use **kwargs, but this will give better docs</span>
<div class="viewcode-block" id="set_printoptions"><a class="viewcode-back" href="../../torch.html#torch.set_printoptions">[docs]</a><span class="k">def</span> <span class="nf">set_printoptions</span><span class="p">(</span>
        <span class="n">precision</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
        <span class="n">threshold</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
        <span class="n">edgeitems</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
        <span class="n">linewidth</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
        <span class="n">profile</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
        <span class="n">sci_mode</span><span class="o">=</span><span class="kc">None</span>
<span class="p">):</span>
    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Set options for printing. Items shamelessly taken from NumPy</span>

<span class="sd">    Args:</span>
<span class="sd">        precision: Number of digits of precision for floating point output</span>
<span class="sd">            (default = 4).</span>
<span class="sd">        threshold: Total number of array elements which trigger summarization</span>
<span class="sd">            rather than full `repr` (default = 1000).</span>
<span class="sd">        edgeitems: Number of array items in summary at beginning and end of</span>
<span class="sd">            each dimension (default = 3).</span>
<span class="sd">        linewidth: The number of characters per line for the purpose of</span>
<span class="sd">            inserting line breaks (default = 80). Thresholded matrices will</span>
<span class="sd">            ignore this parameter.</span>
<span class="sd">        profile: Sane defaults for pretty printing. Can override with any of</span>
<span class="sd">            the above options. (any one of `default`, `short`, `full`)</span>
<span class="sd">        sci_mode: Enable (True) or disable (False) scientific notation. If</span>
<span class="sd">            None (default) is specified, the value is defined by `_Formatter`</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">if</span> <span class="n">profile</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="k">if</span> <span class="n">profile</span> <span class="o">==</span> <span class="s2">&quot;default&quot;</span><span class="p">:</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span> <span class="o">=</span> <span class="mi">4</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">threshold</span> <span class="o">=</span> <span class="mi">1000</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span> <span class="o">=</span> <span class="mi">3</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">linewidth</span> <span class="o">=</span> <span class="mi">80</span>
        <span class="k">elif</span> <span class="n">profile</span> <span class="o">==</span> <span class="s2">&quot;short&quot;</span><span class="p">:</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span> <span class="o">=</span> <span class="mi">2</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">threshold</span> <span class="o">=</span> <span class="mi">1000</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span> <span class="o">=</span> <span class="mi">2</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">linewidth</span> <span class="o">=</span> <span class="mi">80</span>
        <span class="k">elif</span> <span class="n">profile</span> <span class="o">==</span> <span class="s2">&quot;full&quot;</span><span class="p">:</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span> <span class="o">=</span> <span class="mi">4</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">threshold</span> <span class="o">=</span> <span class="n">inf</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span> <span class="o">=</span> <span class="mi">3</span>
            <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">linewidth</span> <span class="o">=</span> <span class="mi">80</span>

    <span class="k">if</span> <span class="n">precision</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span> <span class="o">=</span> <span class="n">precision</span>
    <span class="k">if</span> <span class="n">threshold</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">threshold</span> <span class="o">=</span> <span class="n">threshold</span>
    <span class="k">if</span> <span class="n">edgeitems</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span> <span class="o">=</span> <span class="n">edgeitems</span>
    <span class="k">if</span> <span class="n">linewidth</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">linewidth</span> <span class="o">=</span> <span class="n">linewidth</span>
    <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">sci_mode</span> <span class="o">=</span> <span class="n">sci_mode</span></div>


<span class="k">class</span> <span class="nc">_Formatter</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tensor</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">floating_dtype</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">is_floating_point</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">complex_dtype</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">is_complex</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">int_mode</span> <span class="o">=</span> <span class="kc">True</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">sci_mode</span> <span class="o">=</span> <span class="kc">False</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">max_width</span> <span class="o">=</span> <span class="mi">1</span>

        <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
            <span class="n">tensor_view</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>

        <span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">floating_dtype</span><span class="p">:</span>
            <span class="k">for</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">tensor_view</span><span class="p">:</span>
                <span class="n">value_str</span> <span class="o">=</span> <span class="s1">&#39;</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
                <span class="bp">self</span><span class="o">.</span><span class="n">max_width</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_width</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">value_str</span><span class="p">))</span>

        <span class="k">else</span><span class="p">:</span>
            <span class="n">nonzero_finite_vals</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">masked_select</span><span class="p">(</span><span class="n">tensor_view</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">isfinite</span><span class="p">(</span><span class="n">tensor_view</span><span class="p">)</span> <span class="o">&amp;</span> <span class="n">tensor_view</span><span class="o">.</span><span class="n">ne</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span>

            <span class="k">if</span> <span class="n">nonzero_finite_vals</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="c1"># no valid number, do nothing</span>
                <span class="k">return</span>

            <span class="c1"># Convert to double for easy calculation. HalfTensor overflows with 1e8, and there&#39;s no div() on CPU.</span>
            <span class="n">nonzero_finite_abs</span> <span class="o">=</span> <span class="n">nonzero_finite_vals</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span><span class="o">.</span><span class="n">double</span><span class="p">()</span>
            <span class="n">nonzero_finite_min</span> <span class="o">=</span> <span class="n">nonzero_finite_abs</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">double</span><span class="p">()</span>
            <span class="n">nonzero_finite_max</span> <span class="o">=</span> <span class="n">nonzero_finite_abs</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">double</span><span class="p">()</span>

            <span class="k">for</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">nonzero_finite_vals</span><span class="p">:</span>
                <span class="k">if</span> <span class="n">value</span> <span class="o">!=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">value</span><span class="p">):</span>
                    <span class="bp">self</span><span class="o">.</span><span class="n">int_mode</span> <span class="o">=</span> <span class="kc">False</span>
                    <span class="k">break</span>

            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">int_mode</span><span class="p">:</span>
                <span class="c1"># in int_mode for floats, all numbers are integers, and we append a decimal to nonfinites</span>
                <span class="c1"># to indicate that the tensor is of floating type. add 1 to the len to account for this.</span>
                <span class="k">if</span> <span class="n">nonzero_finite_max</span> <span class="o">/</span> <span class="n">nonzero_finite_min</span> <span class="o">&gt;</span> <span class="mf">1000.</span> <span class="ow">or</span> <span class="n">nonzero_finite_max</span> <span class="o">&gt;</span> <span class="mf">1.e8</span><span class="p">:</span>
                    <span class="bp">self</span><span class="o">.</span><span class="n">sci_mode</span> <span class="o">=</span> <span class="kc">True</span>
                    <span class="k">for</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">nonzero_finite_vals</span><span class="p">:</span>
                        <span class="n">value_str</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;{{:.</span><span class="si">{}</span><span class="s1">e}}&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
                        <span class="bp">self</span><span class="o">.</span><span class="n">max_width</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_width</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">value_str</span><span class="p">))</span>
                <span class="k">else</span><span class="p">:</span>
                    <span class="k">for</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">nonzero_finite_vals</span><span class="p">:</span>
                        <span class="n">value_str</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;</span><span class="si">{:.0f}</span><span class="s1">&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
                        <span class="bp">self</span><span class="o">.</span><span class="n">max_width</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_width</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">value_str</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
            <span class="k">else</span><span class="p">:</span>
                <span class="c1"># Check if scientific representation should be used.</span>
                <span class="k">if</span> <span class="n">nonzero_finite_max</span> <span class="o">/</span> <span class="n">nonzero_finite_min</span> <span class="o">&gt;</span> <span class="mf">1000.</span>\
                        <span class="ow">or</span> <span class="n">nonzero_finite_max</span> <span class="o">&gt;</span> <span class="mf">1.e8</span>\
                        <span class="ow">or</span> <span class="n">nonzero_finite_min</span> <span class="o">&lt;</span> <span class="mf">1.e-4</span><span class="p">:</span>
                    <span class="bp">self</span><span class="o">.</span><span class="n">sci_mode</span> <span class="o">=</span> <span class="kc">True</span>
                    <span class="k">for</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">nonzero_finite_vals</span><span class="p">:</span>
                        <span class="n">value_str</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;{{:.</span><span class="si">{}</span><span class="s1">e}}&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
                        <span class="bp">self</span><span class="o">.</span><span class="n">max_width</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_width</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">value_str</span><span class="p">))</span>
                <span class="k">else</span><span class="p">:</span>
                    <span class="k">for</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">nonzero_finite_vals</span><span class="p">:</span>
                        <span class="n">value_str</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;{{:.</span><span class="si">{}</span><span class="s1">f}}&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
                        <span class="bp">self</span><span class="o">.</span><span class="n">max_width</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_width</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">value_str</span><span class="p">))</span>

        <span class="k">if</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">sci_mode</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">sci_mode</span> <span class="o">=</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">sci_mode</span>

    <span class="k">def</span> <span class="nf">width</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_width</span>

    <span class="k">def</span> <span class="nf">format</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">floating_dtype</span><span class="p">:</span>
            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sci_mode</span><span class="p">:</span>
                <span class="n">ret</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;{{:</span><span class="si">{}</span><span class="s1">.</span><span class="si">{}</span><span class="s1">e}}&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_width</span><span class="p">,</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
            <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">int_mode</span><span class="p">:</span>
                <span class="n">ret</span> <span class="o">=</span> <span class="s1">&#39;</span><span class="si">{:.0f}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
                <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="n">math</span><span class="o">.</span><span class="n">isinf</span><span class="p">(</span><span class="n">value</span><span class="p">)</span> <span class="ow">or</span> <span class="n">math</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">value</span><span class="p">)):</span>
                    <span class="n">ret</span> <span class="o">+=</span> <span class="s1">&#39;.&#39;</span>
            <span class="k">else</span><span class="p">:</span>
                <span class="n">ret</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;{{:.</span><span class="si">{}</span><span class="s1">f}}&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
        <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">complex_dtype</span><span class="p">:</span>
            <span class="n">p</span> <span class="o">=</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">precision</span>
            <span class="n">ret</span> <span class="o">=</span> <span class="s1">&#39;({{:.</span><span class="si">{}</span><span class="s1">f}} {{}} {{:.</span><span class="si">{}</span><span class="s1">f}}j)&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">p</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="s1">&#39;+-&#39;</span><span class="p">[</span><span class="n">value</span><span class="o">.</span><span class="n">imag</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">],</span> <span class="nb">abs</span><span class="p">(</span><span class="n">value</span><span class="o">.</span><span class="n">imag</span><span class="p">))</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">ret</span> <span class="o">=</span> <span class="s1">&#39;</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
        <span class="k">return</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_width</span> <span class="o">-</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">))</span> <span class="o">*</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="n">ret</span>


<span class="k">def</span> <span class="nf">_scalar_str</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">formatter</span><span class="p">):</span>
    <span class="k">return</span> <span class="n">formatter</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">item</span><span class="p">())</span>


<span class="k">def</span> <span class="nf">_vector_str</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indent</span><span class="p">,</span> <span class="n">formatter</span><span class="p">,</span> <span class="n">summarize</span><span class="p">):</span>
    <span class="c1"># length includes spaces and comma between elements</span>
    <span class="n">element_length</span> <span class="o">=</span> <span class="n">formatter</span><span class="o">.</span><span class="n">width</span><span class="p">()</span> <span class="o">+</span> <span class="mi">2</span>
    <span class="n">elements_per_line</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">int</span><span class="p">(</span><span class="n">math</span><span class="o">.</span><span class="n">floor</span><span class="p">((</span><span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">linewidth</span> <span class="o">-</span> <span class="n">indent</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">element_length</span><span class="p">))))</span>
    <span class="n">char_per_line</span> <span class="o">=</span> <span class="n">element_length</span> <span class="o">*</span> <span class="n">elements_per_line</span>

    <span class="k">if</span> <span class="n">summarize</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">:</span>
        <span class="n">data</span> <span class="o">=</span> <span class="p">([</span><span class="n">formatter</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">val</span><span class="p">)</span> <span class="k">for</span> <span class="n">val</span> <span class="ow">in</span> <span class="bp">self</span><span class="p">[:</span><span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()]</span> <span class="o">+</span>
                <span class="p">[</span><span class="s1">&#39; ...&#39;</span><span class="p">]</span> <span class="o">+</span>
                <span class="p">[</span><span class="n">formatter</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">val</span><span class="p">)</span> <span class="k">for</span> <span class="n">val</span> <span class="ow">in</span> <span class="bp">self</span><span class="p">[</span><span class="o">-</span><span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">:]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()])</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">data</span> <span class="o">=</span> <span class="p">[</span><span class="n">formatter</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">val</span><span class="p">)</span> <span class="k">for</span> <span class="n">val</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tolist</span><span class="p">()]</span>

    <span class="n">data_lines</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="n">i</span><span class="p">:</span><span class="n">i</span> <span class="o">+</span> <span class="n">elements_per_line</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">),</span> <span class="n">elements_per_line</span><span class="p">)]</span>
    <span class="n">lines</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">line</span><span class="p">)</span> <span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">data_lines</span><span class="p">]</span>
    <span class="k">return</span> <span class="s1">&#39;[&#39;</span> <span class="o">+</span> <span class="p">(</span><span class="s1">&#39;,&#39;</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39; &#39;</span> <span class="o">*</span> <span class="p">(</span><span class="n">indent</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">lines</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;]&#39;</span>


<span class="k">def</span> <span class="nf">_tensor_str_with_formatter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indent</span><span class="p">,</span> <span class="n">formatter</span><span class="p">,</span> <span class="n">summarize</span><span class="p">):</span>
    <span class="n">dim</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dim</span><span class="p">()</span>

    <span class="k">if</span> <span class="n">dim</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
        <span class="k">return</span> <span class="n">_scalar_str</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">formatter</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">dim</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
        <span class="k">return</span> <span class="n">_vector_str</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indent</span><span class="p">,</span> <span class="n">formatter</span><span class="p">,</span> <span class="n">summarize</span><span class="p">)</span>

    <span class="k">if</span> <span class="n">summarize</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">:</span>
        <span class="n">slices</span> <span class="o">=</span> <span class="p">([</span><span class="n">_tensor_str_with_formatter</span><span class="p">(</span><span class="bp">self</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">indent</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">formatter</span><span class="p">,</span> <span class="n">summarize</span><span class="p">)</span>
                   <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">)]</span> <span class="o">+</span>
                  <span class="p">[</span><span class="s1">&#39;...&#39;</span><span class="p">]</span> <span class="o">+</span>
                  <span class="p">[</span><span class="n">_tensor_str_with_formatter</span><span class="p">(</span><span class="bp">self</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">indent</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">formatter</span><span class="p">,</span> <span class="n">summarize</span><span class="p">)</span>
                   <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">))])</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">slices</span> <span class="o">=</span> <span class="p">[</span><span class="n">_tensor_str_with_formatter</span><span class="p">(</span><span class="bp">self</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">indent</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">formatter</span><span class="p">,</span> <span class="n">summarize</span><span class="p">)</span>
                  <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">))]</span>

    <span class="n">tensor_str</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;,&#39;</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">*</span> <span class="p">(</span><span class="n">dim</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39; &#39;</span> <span class="o">*</span> <span class="p">(</span><span class="n">indent</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">slices</span><span class="p">)</span>
    <span class="k">return</span> <span class="s1">&#39;[&#39;</span> <span class="o">+</span> <span class="n">tensor_str</span> <span class="o">+</span> <span class="s1">&#39;]&#39;</span>


<span class="k">def</span> <span class="nf">_tensor_str</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indent</span><span class="p">):</span>
    <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
        <span class="k">return</span> <span class="s1">&#39;[]&#39;</span>

    <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">has_names</span><span class="p">():</span>
        <span class="c1"># There are two main codepaths (possibly more) that tensor printing goes through:</span>
        <span class="c1"># - tensor data can fit comfortably on screen</span>
        <span class="c1"># - tensor data needs to be summarized</span>
        <span class="c1"># Some of the codepaths don&#39;t fully support named tensors, so we send in</span>
        <span class="c1"># an unnamed tensor to the formatting code as a workaround.</span>
        <span class="bp">self</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>

    <span class="n">summarize</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">&gt;</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">threshold</span>
    <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="ow">is</span> <span class="n">torch</span><span class="o">.</span><span class="n">float16</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="ow">is</span> <span class="n">torch</span><span class="o">.</span><span class="n">bfloat16</span><span class="p">:</span>
        <span class="bp">self</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
    <span class="n">formatter</span> <span class="o">=</span> <span class="n">_Formatter</span><span class="p">(</span><span class="n">get_summarized_data</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="k">if</span> <span class="n">summarize</span> <span class="k">else</span> <span class="bp">self</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">_tensor_str_with_formatter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indent</span><span class="p">,</span> <span class="n">formatter</span><span class="p">,</span> <span class="n">summarize</span><span class="p">)</span>


<span class="k">def</span> <span class="nf">_add_suffixes</span><span class="p">(</span><span class="n">tensor_str</span><span class="p">,</span> <span class="n">suffixes</span><span class="p">,</span> <span class="n">indent</span><span class="p">,</span> <span class="n">force_newline</span><span class="p">):</span>
    <span class="n">tensor_strs</span> <span class="o">=</span> <span class="p">[</span><span class="n">tensor_str</span><span class="p">]</span>
    <span class="n">last_line_len</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">tensor_str</span><span class="p">)</span> <span class="o">-</span> <span class="n">tensor_str</span><span class="o">.</span><span class="n">rfind</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span>
    <span class="k">for</span> <span class="n">suffix</span> <span class="ow">in</span> <span class="n">suffixes</span><span class="p">:</span>
        <span class="n">suffix_len</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">suffix</span><span class="p">)</span>
        <span class="k">if</span> <span class="n">force_newline</span> <span class="ow">or</span> <span class="n">last_line_len</span> <span class="o">+</span> <span class="n">suffix_len</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">&gt;</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">linewidth</span><span class="p">:</span>
            <span class="n">tensor_strs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;,</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39; &#39;</span> <span class="o">*</span> <span class="n">indent</span> <span class="o">+</span> <span class="n">suffix</span><span class="p">)</span>
            <span class="n">last_line_len</span> <span class="o">=</span> <span class="n">indent</span> <span class="o">+</span> <span class="n">suffix_len</span>
            <span class="n">force_newline</span> <span class="o">=</span> <span class="kc">False</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">tensor_strs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;, &#39;</span> <span class="o">+</span> <span class="n">suffix</span><span class="p">)</span>
            <span class="n">last_line_len</span> <span class="o">+=</span> <span class="n">suffix_len</span> <span class="o">+</span> <span class="mi">2</span>
    <span class="n">tensor_strs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;)&#39;</span><span class="p">)</span>
    <span class="k">return</span> <span class="s1">&#39;&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">tensor_strs</span><span class="p">)</span>


<span class="k">def</span> <span class="nf">get_summarized_data</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
    <span class="n">dim</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dim</span><span class="p">()</span>
    <span class="k">if</span> <span class="n">dim</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
        <span class="k">return</span> <span class="bp">self</span>
    <span class="k">if</span> <span class="n">dim</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">((</span><span class="bp">self</span><span class="p">[:</span><span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">],</span> <span class="bp">self</span><span class="p">[</span><span class="o">-</span><span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">:]))</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">return</span> <span class="bp">self</span>
    <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">:</span>
        <span class="n">start</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">)]</span>
        <span class="n">end</span> <span class="o">=</span> <span class="p">([</span><span class="bp">self</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
               <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">edgeitems</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">))])</span>
        <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">get_summarized_data</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">(</span><span class="n">start</span> <span class="o">+</span> <span class="n">end</span><span class="p">)])</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">get_summarized_data</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="bp">self</span><span class="p">])</span>


<span class="k">def</span> <span class="nf">_str</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
    <span class="n">prefix</span> <span class="o">=</span> <span class="s1">&#39;tensor(&#39;</span>
    <span class="n">indent</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">prefix</span><span class="p">)</span>
    <span class="n">suffixes</span> <span class="o">=</span> <span class="p">[]</span>

    <span class="c1"># Note [Print tensor device]:</span>
    <span class="c1"># A general logic here is we only print device when it doesn&#39;t match</span>
    <span class="c1"># the device specified in default tensor type.</span>
    <span class="c1"># Currently torch.set_default_tensor_type() only supports CPU/CUDA, thus</span>
    <span class="c1"># torch._C._get_default_device() only returns either cpu or cuda.</span>
    <span class="c1"># In other cases, we don&#39;t have a way to set them as default yet,</span>
    <span class="c1"># and we should always print out device for them.</span>
    <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="n">type</span> <span class="o">!=</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_get_default_device</span><span class="p">()</span>\
            <span class="ow">or</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s1">&#39;cuda&#39;</span> <span class="ow">and</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">current_device</span><span class="p">()</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="n">index</span><span class="p">):</span>
        <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;device=</span><span class="se">\&#39;</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\&#39;</span><span class="s1">&#39;</span><span class="p">)</span>

    <span class="n">has_default_dtype</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="ow">in</span> <span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">get_default_dtype</span><span class="p">(),</span> <span class="n">torch</span><span class="o">.</span><span class="n">int64</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">bool</span><span class="p">)</span>
    <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_sparse</span><span class="p">:</span>
        <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;size=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)))</span>
        <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;nnz=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_nnz</span><span class="p">()))</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="n">has_default_dtype</span><span class="p">:</span>
            <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;dtype=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">))</span>
        <span class="n">indices_prefix</span> <span class="o">=</span> <span class="s1">&#39;indices=tensor(&#39;</span>
        <span class="n">indices</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_indices</span><span class="p">()</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span>
        <span class="n">indices_str</span> <span class="o">=</span> <span class="n">_tensor_str</span><span class="p">(</span><span class="n">indices</span><span class="p">,</span> <span class="n">indent</span> <span class="o">+</span> <span class="nb">len</span><span class="p">(</span><span class="n">indices_prefix</span><span class="p">))</span>
        <span class="k">if</span> <span class="n">indices</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
            <span class="n">indices_str</span> <span class="o">+=</span> <span class="s1">&#39;, size=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">tuple</span><span class="p">(</span><span class="n">indices</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
        <span class="n">values_prefix</span> <span class="o">=</span> <span class="s1">&#39;values=tensor(&#39;</span>
        <span class="n">values</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_values</span><span class="p">()</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span>
        <span class="n">values_str</span> <span class="o">=</span> <span class="n">_tensor_str</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">indent</span> <span class="o">+</span> <span class="nb">len</span><span class="p">(</span><span class="n">values_prefix</span><span class="p">))</span>
        <span class="k">if</span> <span class="n">values</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
            <span class="n">values_str</span> <span class="o">+=</span> <span class="s1">&#39;, size=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">tuple</span><span class="p">(</span><span class="n">values</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
        <span class="n">tensor_str</span> <span class="o">=</span> <span class="n">indices_prefix</span> <span class="o">+</span> <span class="n">indices_str</span> <span class="o">+</span> <span class="s1">&#39;),</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39; &#39;</span> <span class="o">*</span> <span class="n">indent</span> <span class="o">+</span> <span class="n">values_prefix</span> <span class="o">+</span> <span class="n">values_str</span> <span class="o">+</span> <span class="s1">&#39;)&#39;</span>
    <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_quantized</span><span class="p">:</span>
        <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;size=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)))</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="n">has_default_dtype</span><span class="p">:</span>
            <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;dtype=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">))</span>
        <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;quantization_scheme=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">qscheme</span><span class="p">()))</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">qscheme</span><span class="p">()</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">per_tensor_affine</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">qscheme</span><span class="p">()</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">per_tensor_symmetric</span><span class="p">:</span>
            <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;scale=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">q_scale</span><span class="p">()))</span>
            <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;zero_point=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">q_zero_point</span><span class="p">()))</span>
        <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">qscheme</span><span class="p">()</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">per_channel_affine</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">qscheme</span><span class="p">()</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">per_channel_symmetric</span><span class="p">:</span>
            <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;scale=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">q_per_channel_scales</span><span class="p">()))</span>
            <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;zero_point=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">q_per_channel_zero_points</span><span class="p">()))</span>
            <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;axis=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">q_per_channel_axis</span><span class="p">()))</span>
        <span class="n">tensor_str</span> <span class="o">=</span> <span class="n">_tensor_str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dequantize</span><span class="p">(),</span> <span class="n">indent</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">==</span> <span class="mi">0</span> <span class="ow">and</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_sparse</span><span class="p">:</span>
            <span class="c1"># Explicitly print the shape if it is not (0,), to match NumPy behavior</span>
            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dim</span><span class="p">()</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;size=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)))</span>

            <span class="c1"># In an empty tensor, there are no elements to infer if the dtype</span>
            <span class="c1"># should be int64, so it must be shown explicitly.</span>
            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">!=</span> <span class="n">torch</span><span class="o">.</span><span class="n">get_default_dtype</span><span class="p">():</span>
                <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;dtype=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">))</span>
            <span class="n">tensor_str</span> <span class="o">=</span> <span class="s1">&#39;[]&#39;</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="ow">not</span> <span class="n">has_default_dtype</span><span class="p">:</span>
                <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;dtype=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">))</span>

            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">layout</span> <span class="o">!=</span> <span class="n">torch</span><span class="o">.</span><span class="n">strided</span><span class="p">:</span>
                <span class="n">tensor_str</span> <span class="o">=</span> <span class="n">_tensor_str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">to_dense</span><span class="p">(),</span> <span class="n">indent</span><span class="p">)</span>
            <span class="k">else</span><span class="p">:</span>
                <span class="n">tensor_str</span> <span class="o">=</span> <span class="n">_tensor_str</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indent</span><span class="p">)</span>

    <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">layout</span> <span class="o">!=</span> <span class="n">torch</span><span class="o">.</span><span class="n">strided</span><span class="p">:</span>
        <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;layout=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">layout</span><span class="p">))</span>

    <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">grad_fn</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">name</span> <span class="o">=</span> <span class="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">grad_fn</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span>
        <span class="k">if</span> <span class="n">name</span> <span class="o">==</span> <span class="s1">&#39;CppFunction&#39;</span><span class="p">:</span>
            <span class="n">name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">grad_fn</span><span class="o">.</span><span class="n">name</span><span class="p">()</span><span class="o">.</span><span class="n">rsplit</span><span class="p">(</span><span class="s1">&#39;::&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
        <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;grad_fn=&lt;</span><span class="si">{}</span><span class="s1">&gt;&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">name</span><span class="p">))</span>
    <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">requires_grad</span><span class="p">:</span>
        <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;requires_grad=True&#39;</span><span class="p">)</span>

    <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">has_names</span><span class="p">():</span>
        <span class="n">suffixes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;names=</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">names</span><span class="p">))</span>

    <span class="k">return</span> <span class="n">_add_suffixes</span><span class="p">(</span><span class="n">prefix</span> <span class="o">+</span> <span class="n">tensor_str</span><span class="p">,</span> <span class="n">suffixes</span><span class="p">,</span> <span class="n">indent</span><span class="p">,</span> <span class="n">force_newline</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">is_sparse</span><span class="p">)</span>
</pre></div>

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